Serve as the primary technical advisor for customer engagements, building trusted relationships with executive leadership, technical stakeholders, and business owners.
Lead technical discovery sessions, solution workshops, and architecture discussions to define customer objectives and implementation strategies.
Translate business priorities into scalable AI-enabled software solutions and technical roadmaps.
Advise customers on AI adoption strategies, solution architecture, governance, and operational readiness.
Communicate complex technical concepts, trade-offs, and implementation risks to both technical and non-technical audiences.
Support business development activities through technical presentations, demonstrations, proof-of-concepts (POCs), proposals, and solution briefings.
Lead cross-functional engineering teams responsible for delivering enterprise AI and software solutions.
Provide technical direction throughout the full software development lifecycle, from architecture through deployment and operational support.
Guide engineering teams in designing secure, scalable, maintainable, and high-performing software systems.
Lead architecture reviews, design discussions, sprint planning, technical decision-making, and engineering governance.
Establish engineering standards, development practices, quality metrics, and delivery processes across engagements.
Remove technical blockers, manage delivery risks, and ensure successful execution across multiple projects or workstreams.
Mentor engineers through architecture guidance, code reviews, technical coaching, and career development.
Architect and oversee the development of AI-enabled applications, intelligent automation solutions, and modern software platforms.
Lead the design and implementation of solutions leveraging large language models (LLMs), retrieval-augmented generation (RAG), agentic AI, machine learning, and other emerging AI technologies.
Guide the design of scalable data pipelines, knowledge retrieval systems, APIs, microservices, and enterprise integrations.
Establish best practices for prompt engineering, AI evaluation, model governance, human-in-the-loop workflows, and responsible AI.
Define engineering approaches that balance scalability, performance, security, reliability, governance, and cost.
Review production-quality code and ensure adherence to software engineering best practices.
Drive implementation of CI/CD pipelines, automated testing, monitoring, logging, observability, and operational excellence.
Develop reusable frameworks, technical accelerators, documentation, and engineering standards that improve delivery across programs.
Lead multiple engineering initiatives while ensuring consistent delivery quality across teams.
Coordinate cross-functional and geographically distributed engineering teams, including hybrid onshore/offshore delivery models.
Establish delivery governance, resource planning, risk management, stakeholder communications, and project health reporting.
Contribute to organizational engineering strategy, AI capability development, and technical innovation.
Promote continuous improvement through engineering best practices, reusable assets, and knowledge sharing.
Stay current on emerging AI technologies, cloud platforms, software engineering trends, and industry best practices.
Requirements
Bachelor's degree in Computer Science, Software Engineering, Data Science, Information Systems, or a related technical discipline (or equivalent experience).
7+ years of experience in software engineering, AI engineering, machine learning, data engineering, solution architecture, or related technical roles.
Demonstrated experience leading engineering teams delivering enterprise software solutions.
Experience designing, building, and deploying AI/ML or Generative AI solutions in production environments.